Compare Models

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GPT 4.1 NanoMistral Large 4 OSS


Vals IndexGDP-weighted benchmark	N/A	56.42%±1.26
Legal Research BenchAgentic US legal research	N/A	35.58%±3.33
Finance Agent v2.1Core financial analyst tasks	N/A	61.72%±2.05
Tax Agent BenchAgentic US corporate tax research	N/A	27.33%±2.95
Terminal-Bench 4.0Frontier-difficulty terminal tasks	N/A	26.26%±5.13
Vibe Code Bench v1.1Building web apps from scratch	N/A	81.56%±3.29

Benchmarks

Vals Index *

GPT 4.1 Nano

N/A

Mistral Large 4 OSS

0.00%± 1.26

(32/32)

Legal Research Bench *

GPT 4.1 Nano

N/A

Mistral Large 4 OSS

0.00%± 3.33

(89/89)

Finance Agent v2.1 *

GPT 4.1 Nano

N/A

Mistral Large 4 OSS

0.00%± 2.05

(35/35)

Tax Agent Bench *

GPT 4.1 Nano

N/A

Mistral Large 4 OSS

0.00%± 2.95

(80/80)

Terminal-Bench 4.0

GPT 4.1 Nano

N/A

Mistral Large 4 OSS

0.00%± 5.13

(59/59)

Vibe Code Bench v1.1 *

GPT 4.1 Nano

N/A

Mistral Large 4 OSS

0.00%± 3.29

(123/123)

Overall performance

Performance on the Vals Index, a GDP-weighted aggregation of tasks across finance, coding, and law

•2026-10-29

GPT 4.1 Nano Mistral Large 4 OSS

Comparison by Industry

Model performance on different sections of the economy.

Legal

61.06%

vs.

25.70%

Finance

56.79%

vs.

52.58%

Academic

56.43%

vs.

N/A

Coding

42.72%

vs.

53.91%

Cost Analysis

Per task and per token model pricing.

Vals Index · USD

N/A

$3.717

Cost / TestVals Index

N/A

vs.

$3.717

Input Cost/ 1M Tokens

$0.10

vs.

$0.70

Input Cache Read/ 1M Tokens

$0.025

vs.

$0.07

Output Cost/ 1M Tokens

$0.40

vs.

$2.10

Model Metadata

Basic information about each model.


Model provider	OpenAI	Mistral AI
Latency	N/A	2868.04s
Cost (In/Out)	$0.1 / $0.4	$0.7 / $2.1
Context Window	1M	1M
Max Output Token	33k	256k
Input Modality